Virtualization as a platform for resource-intensive applications, such as MapReduce (MR), has been the subject of many studies in the last years, as it has brought benefits such as better manageability, overall resource utilization, security and scalability. Nevertheless, because of the performance overheads, virtualization has traditionally been avoided in computing environments where performance is a critical factor. In this context, container-based virtualization can be considered a lightweight alternative to the traditional hypervisor-based virtualization systems. In fact, there is a trend towards using containers in MR clusters in order to provide resource sharing and performance isolation (e.g., Mesos and YARN). However, there are still no studies evaluating the performance overhead of the current container-based systems and their ability to provide performance isolation when running MR applications. In this work, we conducted experiments to effectively compare and contrast the current container-based systems (Linux VServer, OpenVZ and Linux Containers (LXC)) in terms of performance and manageability when running on MR clusters. Our results showed that although all container-based systems reach a near-native performance for MapReduce workloads, LXC is the one that offers the best relationship between performance and management capabilities (specially regarding to performance isolation).
The popularity of Cloud computing due to the increasing number of customers has led Cloud providers to adopt resource-sharing solutions to meet growing demand for infrastructure resources. As the adoption of resourcesharing/consolidation in Cloud computing became arguably a well-established solution, the ability the underlying virtualization systems of preventing performance interferences from customers must also be understood. Virtualization systems based on containers, such as LXC, are the basis of the next-generation of Cloud computing and have become the most popular solution under PaaS/IaaS Cloud platforms with the rise of Docker-an open platform for developers and sysadmins to build, ship, and run distributed applications. Such platforms have enticed many attentions globally, since they leverage container-based virtualization systems to offer high scalability while low performance overheads; the performance might be solely aggravated if the customers' workloads are consolidated onto the same hardware and the isolation layer does not properly isolate the shared resources. Performance isolation is an inherent concern of such systems due to the nature as they are conceived and is still an unexplored and open research topic; the consequences might influence in the adoption under shared Cloud computing platforms where Quality-of-Service is a crucial factor that cannot be disregarded. In this paper we analyze the performance interference suffered by disk-intensive workloads within very noisy-perturbed containers (different hardware components stressed). Our results show workload combinations whose performance degradation goes up to 38%, but in contrast we expose a workload-balanced scenario wherein the performance does not suffer any interference.
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